论文标题
D-Graph：AI辅助设计概念探索图
D-Graph: AI-Assisted Design Concept Exploration Graph
论文作者
论文摘要
我们提供了一个AI辅助搜索工具，即“设计概念探索图”（“ D-Graph”）。它有助于汽车设计师创建一个原始的设计概念词组，即两种传达产品美学的形容词的组合。 d-graph从概念网知识图中检索形容词，因为节点是在用户探索单词时在动态可扩展的3D图中可视化它们的。检索算法通过从大型文本语料库中排除过度使用的单词来帮助查找独特的单词，而在组合中使用Conceptnet NubmegBatch单词嵌入的余弦相似性，两者之间的单词过于相似。我们与汽车设计领域参与者进行的实验，该实验同时使用了拟议的D-Graph和基线工具来设计概念概念式 - 创建任务，这表明参与者对他们创建的短语的自我评估有积极的差异，尽管并不重要。专家对短语的评估没有显示出显着差异。在设计概念概念短语中的两个单词的余弦相似性与专家评估之间的负相关性很大。我们的定性分析提出了该工具进一步开发的指示，该方向应帮助用户遵守创建由计算语言原理支持的复合短语的策略。
We present an AI-assisted search tool, the "Design Concept Exploration Graph" ("D-Graph"). It assists automotive designers in creating an original design-concept phrase, that is, a combination of two adjectives that conveys product aesthetics. D-Graph retrieves adjectives from a ConceptNet knowledge graph as nodes and visualizes them in a dynamically scalable 3D graph as users explore words. The retrieval algorithm helps in finding unique words by ruling out overused words on the basis of word frequency from a large text corpus and words that are too similar between the two in a combination using the cosine similarity from ConceptNet Numberbatch word embeddings. Our experiment with participants in the automotive design field that used both the proposed D-Graph and a baseline tool for design-concept-phrase creation tasks suggested a positive difference in participants' self-evaluation on the phrases they created, though not significant. Experts' evaluations on the phrases did not show significant differences. Negative correlations between the cosine similarity of the two words in a design-concept phrase and the experts' evaluation were significant. Our qualitative analysis suggested the directions for further development of the tool that should help users in adhering to the strategy of creating compound phrases supported by computational linguistic principles.
